Overview

Dataset statistics

Number of variables133
Number of observations4920
Missing cells0
Missing cells (%)0.0%
Duplicate rows304
Duplicate rows (%)6.2%
Total size in memory5.0 MiB
Average record size in memory1.0 KiB

Variable types

Categorical133

Alerts

fluid_overload has constant value "0" Constant
Dataset has 304 (6.2%) duplicate rowsDuplicates
nodal_skin_eruptions is highly correlated with dischromic _patchesHigh correlation
continuous_sneezing is highly correlated with shivering and 7 other fieldsHigh correlation
shivering is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
chills is highly correlated with high_fever and 2 other fieldsHigh correlation
stomach_pain is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
acidity is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
ulcers_on_tongue is highly correlated with stomach_pain and 1 other fieldsHigh correlation
muscle_wasting is highly correlated with patches_in_throat and 1 other fieldsHigh correlation
vomiting is highly correlated with nauseaHigh correlation
burning_micturition is highly correlated with spotting_ urination and 3 other fieldsHigh correlation
spotting_ urination is highly correlated with stomach_pain and 1 other fieldsHigh correlation
weight_gain is highly correlated with cold_hands_and_feets and 8 other fieldsHigh correlation
anxiety is highly correlated with blurred_and_distorted_vision and 3 other fieldsHigh correlation
cold_hands_and_feets is highly correlated with weight_gain and 8 other fieldsHigh correlation
mood_swings is highly correlated with weight_gain and 7 other fieldsHigh correlation
weight_loss is highly correlated with restlessnessHigh correlation
restlessness is highly correlated with weight_loss and 4 other fieldsHigh correlation
patches_in_throat is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
irregular_sugar_level is highly correlated with restlessness and 4 other fieldsHigh correlation
cough is highly correlated with breathlessness and 2 other fieldsHigh correlation
high_fever is highly correlated with chillsHigh correlation
sunken_eyes is highly correlated with dehydrationHigh correlation
breathlessness is highly correlated with cough and 3 other fieldsHigh correlation
sweating is highly correlated with breathlessness and 1 other fieldsHigh correlation
dehydration is highly correlated with sunken_eyesHigh correlation
indigestion is highly correlated with passage_of_gases and 2 other fieldsHigh correlation
yellowish_skin is highly correlated with dark_urine and 3 other fieldsHigh correlation
dark_urine is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
nausea is highly correlated with vomitingHigh correlation
loss_of_appetite is highly correlated with yellowish_skin and 1 other fieldsHigh correlation
pain_behind_the_eyes is highly correlated with back_pain and 1 other fieldsHigh correlation
back_pain is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
constipation is highly correlated with pain_during_bowel_movements and 5 other fieldsHigh correlation
abdominal_pain is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
mild_fever is highly correlated with swelled_lymph_nodes and 1 other fieldsHigh correlation
yellow_urine is highly correlated with receiving_blood_transfusion and 1 other fieldsHigh correlation
yellowing_of_eyes is highly correlated with yellowish_skin and 3 other fieldsHigh correlation
acute_liver_failure is highly correlated with coma and 1 other fieldsHigh correlation
swelling_of_stomach is highly correlated with distention_of_abdomen and 2 other fieldsHigh correlation
swelled_lymph_nodes is highly correlated with mild_fever and 9 other fieldsHigh correlation
malaise is highly correlated with chills and 3 other fieldsHigh correlation
blurred_and_distorted_vision is highly correlated with anxiety and 9 other fieldsHigh correlation
phlegm is highly correlated with chills and 13 other fieldsHigh correlation
throat_irritation is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
redness_of_eyes is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
sinus_pressure is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
runny_nose is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
congestion is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
chest_pain is highly correlated with cough and 2 other fieldsHigh correlation
weakness_in_limbs is highly correlated with back_pain and 3 other fieldsHigh correlation
fast_heart_rate is highly correlated with sweating and 1 other fieldsHigh correlation
pain_during_bowel_movements is highly correlated with constipation and 3 other fieldsHigh correlation
pain_in_anal_region is highly correlated with constipation and 3 other fieldsHigh correlation
bloody_stool is highly correlated with constipation and 3 other fieldsHigh correlation
irritation_in_anus is highly correlated with constipation and 3 other fieldsHigh correlation
neck_pain is highly correlated with weakness_in_limbs and 2 other fieldsHigh correlation
dizziness is highly correlated with weight_gain and 8 other fieldsHigh correlation
cramps is highly correlated with bruising and 4 other fieldsHigh correlation
bruising is highly correlated with cramps and 4 other fieldsHigh correlation
obesity is highly correlated with irregular_sugar_level and 7 other fieldsHigh correlation
swollen_legs is highly correlated with cramps and 4 other fieldsHigh correlation
swollen_blood_vessels is highly correlated with cramps and 4 other fieldsHigh correlation
puffy_face_and_eyes is highly correlated with weight_gain and 8 other fieldsHigh correlation
enlarged_thyroid is highly correlated with weight_gain and 8 other fieldsHigh correlation
brittle_nails is highly correlated with weight_gain and 8 other fieldsHigh correlation
swollen_extremeties is highly correlated with weight_gain and 8 other fieldsHigh correlation
excessive_hunger is highly correlated with restlessness and 2 other fieldsHigh correlation
extra_marital_contacts is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
drying_and_tingling_lips is highly correlated with anxiety and 3 other fieldsHigh correlation
slurred_speech is highly correlated with anxiety and 3 other fieldsHigh correlation
knee_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
hip_joint_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
muscle_weakness is highly correlated with movement_stiffnessHigh correlation
stiff_neck is highly correlated with movement_stiffness and 1 other fieldsHigh correlation
swelling_joints is highly correlated with knee_pain and 3 other fieldsHigh correlation
movement_stiffness is highly correlated with muscle_weakness and 3 other fieldsHigh correlation
spinning_movements is highly correlated with loss_of_balance and 1 other fieldsHigh correlation
loss_of_balance is highly correlated with weakness_in_limbs and 4 other fieldsHigh correlation
unsteadiness is highly correlated with spinning_movements and 1 other fieldsHigh correlation
weakness_of_one_body_side is highly correlated with altered_sensoriumHigh correlation
loss_of_smell is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
bladder_discomfort is highly correlated with burning_micturition and 2 other fieldsHigh correlation
foul_smell_of urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
continuous_feel_of_urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
passage_of_gases is highly correlated with indigestion and 1 other fieldsHigh correlation
internal_itching is highly correlated with indigestion and 1 other fieldsHigh correlation
toxic_look_(typhos) is highly correlated with constipation and 1 other fieldsHigh correlation
depression is highly correlated with weight_gain and 7 other fieldsHigh correlation
irritability is highly correlated with mood_swings and 4 other fieldsHigh correlation
altered_sensorium is highly correlated with weakness_of_one_body_sideHigh correlation
red_spots_over_body is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
belly_pain is highly correlated with constipation and 1 other fieldsHigh correlation
abnormal_menstruation is highly correlated with weight_gain and 7 other fieldsHigh correlation
dischromic _patches is highly correlated with nodal_skin_eruptionsHigh correlation
watering_from_eyes is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
increased_appetite is highly correlated with restlessness and 4 other fieldsHigh correlation
polyuria is highly correlated with restlessness and 4 other fieldsHigh correlation
family_history is highly correlated with mucoid_sputumHigh correlation
mucoid_sputum is highly correlated with family_historyHigh correlation
rusty_sputum is highly correlated with phlegm and 1 other fieldsHigh correlation
lack_of_concentration is highly correlated with dizziness and 1 other fieldsHigh correlation
visual_disturbances is highly correlated with acidity and 4 other fieldsHigh correlation
receiving_blood_transfusion is highly correlated with yellow_urine and 1 other fieldsHigh correlation
receiving_unsterile_injections is highly correlated with yellow_urine and 1 other fieldsHigh correlation
coma is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
stomach_bleeding is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
distention_of_abdomen is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
history_of_alcohol_consumption is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
fluid_overload.1 is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
blood_in_sputum is highly correlated with mild_fever and 2 other fieldsHigh correlation
prominent_veins_on_calf is highly correlated with cramps and 4 other fieldsHigh correlation
palpitations is highly correlated with anxiety and 3 other fieldsHigh correlation
painful_walking is highly correlated with knee_pain and 3 other fieldsHigh correlation
pus_filled_pimples is highly correlated with blackheads and 1 other fieldsHigh correlation
blackheads is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
scurring is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
skin_peeling is highly correlated with silver_like_dusting and 2 other fieldsHigh correlation
silver_like_dusting is highly correlated with skin_peeling and 2 other fieldsHigh correlation
small_dents_in_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
inflammatory_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
blister is highly correlated with red_sore_around_nose and 1 other fieldsHigh correlation
red_sore_around_nose is highly correlated with blister and 1 other fieldsHigh correlation
yellow_crust_ooze is highly correlated with blister and 1 other fieldsHigh correlation
nodal_skin_eruptions is highly correlated with dischromic _patchesHigh correlation
continuous_sneezing is highly correlated with shivering and 7 other fieldsHigh correlation
shivering is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
chills is highly correlated with high_fever and 2 other fieldsHigh correlation
stomach_pain is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
acidity is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
ulcers_on_tongue is highly correlated with stomach_pain and 1 other fieldsHigh correlation
muscle_wasting is highly correlated with patches_in_throat and 1 other fieldsHigh correlation
vomiting is highly correlated with nauseaHigh correlation
burning_micturition is highly correlated with spotting_ urination and 3 other fieldsHigh correlation
spotting_ urination is highly correlated with stomach_pain and 1 other fieldsHigh correlation
weight_gain is highly correlated with cold_hands_and_feets and 8 other fieldsHigh correlation
anxiety is highly correlated with blurred_and_distorted_vision and 3 other fieldsHigh correlation
cold_hands_and_feets is highly correlated with weight_gain and 8 other fieldsHigh correlation
mood_swings is highly correlated with weight_gain and 7 other fieldsHigh correlation
weight_loss is highly correlated with restlessnessHigh correlation
restlessness is highly correlated with weight_loss and 4 other fieldsHigh correlation
patches_in_throat is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
irregular_sugar_level is highly correlated with restlessness and 4 other fieldsHigh correlation
cough is highly correlated with breathlessness and 2 other fieldsHigh correlation
high_fever is highly correlated with chillsHigh correlation
sunken_eyes is highly correlated with dehydrationHigh correlation
breathlessness is highly correlated with cough and 3 other fieldsHigh correlation
sweating is highly correlated with breathlessness and 1 other fieldsHigh correlation
dehydration is highly correlated with sunken_eyesHigh correlation
indigestion is highly correlated with passage_of_gases and 2 other fieldsHigh correlation
yellowish_skin is highly correlated with dark_urine and 3 other fieldsHigh correlation
dark_urine is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
nausea is highly correlated with vomitingHigh correlation
loss_of_appetite is highly correlated with yellowish_skin and 1 other fieldsHigh correlation
pain_behind_the_eyes is highly correlated with back_pain and 1 other fieldsHigh correlation
back_pain is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
constipation is highly correlated with pain_during_bowel_movements and 5 other fieldsHigh correlation
abdominal_pain is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
mild_fever is highly correlated with swelled_lymph_nodes and 1 other fieldsHigh correlation
yellow_urine is highly correlated with receiving_blood_transfusion and 1 other fieldsHigh correlation
yellowing_of_eyes is highly correlated with yellowish_skin and 3 other fieldsHigh correlation
acute_liver_failure is highly correlated with coma and 1 other fieldsHigh correlation
swelling_of_stomach is highly correlated with distention_of_abdomen and 2 other fieldsHigh correlation
swelled_lymph_nodes is highly correlated with mild_fever and 9 other fieldsHigh correlation
malaise is highly correlated with chills and 3 other fieldsHigh correlation
blurred_and_distorted_vision is highly correlated with anxiety and 9 other fieldsHigh correlation
phlegm is highly correlated with chills and 13 other fieldsHigh correlation
throat_irritation is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
redness_of_eyes is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
sinus_pressure is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
runny_nose is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
congestion is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
chest_pain is highly correlated with cough and 2 other fieldsHigh correlation
weakness_in_limbs is highly correlated with back_pain and 3 other fieldsHigh correlation
fast_heart_rate is highly correlated with sweating and 1 other fieldsHigh correlation
pain_during_bowel_movements is highly correlated with constipation and 3 other fieldsHigh correlation
pain_in_anal_region is highly correlated with constipation and 3 other fieldsHigh correlation
bloody_stool is highly correlated with constipation and 3 other fieldsHigh correlation
irritation_in_anus is highly correlated with constipation and 3 other fieldsHigh correlation
neck_pain is highly correlated with weakness_in_limbs and 2 other fieldsHigh correlation
dizziness is highly correlated with weight_gain and 8 other fieldsHigh correlation
cramps is highly correlated with bruising and 4 other fieldsHigh correlation
bruising is highly correlated with cramps and 4 other fieldsHigh correlation
obesity is highly correlated with irregular_sugar_level and 7 other fieldsHigh correlation
swollen_legs is highly correlated with cramps and 4 other fieldsHigh correlation
swollen_blood_vessels is highly correlated with cramps and 4 other fieldsHigh correlation
puffy_face_and_eyes is highly correlated with weight_gain and 8 other fieldsHigh correlation
enlarged_thyroid is highly correlated with weight_gain and 8 other fieldsHigh correlation
brittle_nails is highly correlated with weight_gain and 8 other fieldsHigh correlation
swollen_extremeties is highly correlated with weight_gain and 8 other fieldsHigh correlation
excessive_hunger is highly correlated with restlessness and 2 other fieldsHigh correlation
extra_marital_contacts is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
drying_and_tingling_lips is highly correlated with anxiety and 3 other fieldsHigh correlation
slurred_speech is highly correlated with anxiety and 3 other fieldsHigh correlation
knee_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
hip_joint_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
muscle_weakness is highly correlated with movement_stiffnessHigh correlation
stiff_neck is highly correlated with movement_stiffness and 1 other fieldsHigh correlation
swelling_joints is highly correlated with knee_pain and 3 other fieldsHigh correlation
movement_stiffness is highly correlated with muscle_weakness and 3 other fieldsHigh correlation
spinning_movements is highly correlated with loss_of_balance and 1 other fieldsHigh correlation
loss_of_balance is highly correlated with weakness_in_limbs and 4 other fieldsHigh correlation
unsteadiness is highly correlated with spinning_movements and 1 other fieldsHigh correlation
weakness_of_one_body_side is highly correlated with altered_sensoriumHigh correlation
loss_of_smell is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
bladder_discomfort is highly correlated with burning_micturition and 2 other fieldsHigh correlation
foul_smell_of urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
continuous_feel_of_urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
passage_of_gases is highly correlated with indigestion and 1 other fieldsHigh correlation
internal_itching is highly correlated with indigestion and 1 other fieldsHigh correlation
toxic_look_(typhos) is highly correlated with constipation and 1 other fieldsHigh correlation
depression is highly correlated with weight_gain and 7 other fieldsHigh correlation
irritability is highly correlated with mood_swings and 4 other fieldsHigh correlation
altered_sensorium is highly correlated with weakness_of_one_body_sideHigh correlation
red_spots_over_body is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
belly_pain is highly correlated with constipation and 1 other fieldsHigh correlation
abnormal_menstruation is highly correlated with weight_gain and 7 other fieldsHigh correlation
dischromic _patches is highly correlated with nodal_skin_eruptionsHigh correlation
watering_from_eyes is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
increased_appetite is highly correlated with restlessness and 4 other fieldsHigh correlation
polyuria is highly correlated with restlessness and 4 other fieldsHigh correlation
family_history is highly correlated with mucoid_sputumHigh correlation
mucoid_sputum is highly correlated with family_historyHigh correlation
rusty_sputum is highly correlated with phlegm and 1 other fieldsHigh correlation
lack_of_concentration is highly correlated with dizziness and 1 other fieldsHigh correlation
visual_disturbances is highly correlated with acidity and 4 other fieldsHigh correlation
receiving_blood_transfusion is highly correlated with yellow_urine and 1 other fieldsHigh correlation
receiving_unsterile_injections is highly correlated with yellow_urine and 1 other fieldsHigh correlation
coma is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
stomach_bleeding is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
distention_of_abdomen is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
history_of_alcohol_consumption is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
fluid_overload.1 is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
blood_in_sputum is highly correlated with mild_fever and 2 other fieldsHigh correlation
prominent_veins_on_calf is highly correlated with cramps and 4 other fieldsHigh correlation
palpitations is highly correlated with anxiety and 3 other fieldsHigh correlation
painful_walking is highly correlated with knee_pain and 3 other fieldsHigh correlation
pus_filled_pimples is highly correlated with blackheads and 1 other fieldsHigh correlation
blackheads is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
scurring is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
skin_peeling is highly correlated with silver_like_dusting and 2 other fieldsHigh correlation
silver_like_dusting is highly correlated with skin_peeling and 2 other fieldsHigh correlation
small_dents_in_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
inflammatory_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
blister is highly correlated with red_sore_around_nose and 1 other fieldsHigh correlation
red_sore_around_nose is highly correlated with blister and 1 other fieldsHigh correlation
yellow_crust_ooze is highly correlated with blister and 1 other fieldsHigh correlation
nodal_skin_eruptions is highly correlated with dischromic _patchesHigh correlation
continuous_sneezing is highly correlated with shivering and 7 other fieldsHigh correlation
shivering is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
chills is highly correlated with high_fever and 2 other fieldsHigh correlation
stomach_pain is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
acidity is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
ulcers_on_tongue is highly correlated with stomach_pain and 1 other fieldsHigh correlation
muscle_wasting is highly correlated with patches_in_throat and 1 other fieldsHigh correlation
vomiting is highly correlated with nauseaHigh correlation
burning_micturition is highly correlated with spotting_ urination and 3 other fieldsHigh correlation
spotting_ urination is highly correlated with stomach_pain and 1 other fieldsHigh correlation
weight_gain is highly correlated with cold_hands_and_feets and 8 other fieldsHigh correlation
anxiety is highly correlated with blurred_and_distorted_vision and 3 other fieldsHigh correlation
cold_hands_and_feets is highly correlated with weight_gain and 8 other fieldsHigh correlation
mood_swings is highly correlated with weight_gain and 7 other fieldsHigh correlation
weight_loss is highly correlated with restlessnessHigh correlation
restlessness is highly correlated with weight_loss and 4 other fieldsHigh correlation
patches_in_throat is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
irregular_sugar_level is highly correlated with restlessness and 4 other fieldsHigh correlation
cough is highly correlated with breathlessness and 2 other fieldsHigh correlation
high_fever is highly correlated with chillsHigh correlation
sunken_eyes is highly correlated with dehydrationHigh correlation
breathlessness is highly correlated with cough and 3 other fieldsHigh correlation
sweating is highly correlated with breathlessness and 1 other fieldsHigh correlation
dehydration is highly correlated with sunken_eyesHigh correlation
indigestion is highly correlated with passage_of_gases and 2 other fieldsHigh correlation
yellowish_skin is highly correlated with dark_urine and 3 other fieldsHigh correlation
dark_urine is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
nausea is highly correlated with vomitingHigh correlation
loss_of_appetite is highly correlated with yellowish_skin and 1 other fieldsHigh correlation
pain_behind_the_eyes is highly correlated with back_pain and 1 other fieldsHigh correlation
back_pain is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
constipation is highly correlated with pain_during_bowel_movements and 5 other fieldsHigh correlation
abdominal_pain is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
mild_fever is highly correlated with swelled_lymph_nodes and 1 other fieldsHigh correlation
yellow_urine is highly correlated with receiving_blood_transfusion and 1 other fieldsHigh correlation
yellowing_of_eyes is highly correlated with yellowish_skin and 3 other fieldsHigh correlation
acute_liver_failure is highly correlated with coma and 1 other fieldsHigh correlation
swelling_of_stomach is highly correlated with distention_of_abdomen and 2 other fieldsHigh correlation
swelled_lymph_nodes is highly correlated with mild_fever and 9 other fieldsHigh correlation
malaise is highly correlated with chills and 3 other fieldsHigh correlation
blurred_and_distorted_vision is highly correlated with anxiety and 9 other fieldsHigh correlation
phlegm is highly correlated with chills and 13 other fieldsHigh correlation
throat_irritation is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
redness_of_eyes is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
sinus_pressure is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
runny_nose is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
congestion is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
chest_pain is highly correlated with cough and 2 other fieldsHigh correlation
weakness_in_limbs is highly correlated with back_pain and 3 other fieldsHigh correlation
fast_heart_rate is highly correlated with sweating and 1 other fieldsHigh correlation
pain_during_bowel_movements is highly correlated with constipation and 3 other fieldsHigh correlation
pain_in_anal_region is highly correlated with constipation and 3 other fieldsHigh correlation
bloody_stool is highly correlated with constipation and 3 other fieldsHigh correlation
irritation_in_anus is highly correlated with constipation and 3 other fieldsHigh correlation
neck_pain is highly correlated with weakness_in_limbs and 2 other fieldsHigh correlation
dizziness is highly correlated with weight_gain and 8 other fieldsHigh correlation
cramps is highly correlated with bruising and 4 other fieldsHigh correlation
bruising is highly correlated with cramps and 4 other fieldsHigh correlation
obesity is highly correlated with irregular_sugar_level and 7 other fieldsHigh correlation
swollen_legs is highly correlated with cramps and 4 other fieldsHigh correlation
swollen_blood_vessels is highly correlated with cramps and 4 other fieldsHigh correlation
puffy_face_and_eyes is highly correlated with weight_gain and 8 other fieldsHigh correlation
enlarged_thyroid is highly correlated with weight_gain and 8 other fieldsHigh correlation
brittle_nails is highly correlated with weight_gain and 8 other fieldsHigh correlation
swollen_extremeties is highly correlated with weight_gain and 8 other fieldsHigh correlation
excessive_hunger is highly correlated with restlessness and 2 other fieldsHigh correlation
extra_marital_contacts is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
drying_and_tingling_lips is highly correlated with anxiety and 3 other fieldsHigh correlation
slurred_speech is highly correlated with anxiety and 3 other fieldsHigh correlation
knee_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
hip_joint_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
muscle_weakness is highly correlated with movement_stiffnessHigh correlation
stiff_neck is highly correlated with movement_stiffness and 1 other fieldsHigh correlation
swelling_joints is highly correlated with knee_pain and 3 other fieldsHigh correlation
movement_stiffness is highly correlated with muscle_weakness and 3 other fieldsHigh correlation
spinning_movements is highly correlated with loss_of_balance and 1 other fieldsHigh correlation
loss_of_balance is highly correlated with weakness_in_limbs and 4 other fieldsHigh correlation
unsteadiness is highly correlated with spinning_movements and 1 other fieldsHigh correlation
weakness_of_one_body_side is highly correlated with altered_sensoriumHigh correlation
loss_of_smell is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
bladder_discomfort is highly correlated with burning_micturition and 2 other fieldsHigh correlation
foul_smell_of urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
continuous_feel_of_urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
passage_of_gases is highly correlated with indigestion and 1 other fieldsHigh correlation
internal_itching is highly correlated with indigestion and 1 other fieldsHigh correlation
toxic_look_(typhos) is highly correlated with constipation and 1 other fieldsHigh correlation
depression is highly correlated with weight_gain and 7 other fieldsHigh correlation
irritability is highly correlated with mood_swings and 4 other fieldsHigh correlation
altered_sensorium is highly correlated with weakness_of_one_body_sideHigh correlation
red_spots_over_body is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
belly_pain is highly correlated with constipation and 1 other fieldsHigh correlation
abnormal_menstruation is highly correlated with weight_gain and 7 other fieldsHigh correlation
dischromic _patches is highly correlated with nodal_skin_eruptionsHigh correlation
watering_from_eyes is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
increased_appetite is highly correlated with restlessness and 4 other fieldsHigh correlation
polyuria is highly correlated with restlessness and 4 other fieldsHigh correlation
family_history is highly correlated with mucoid_sputumHigh correlation
mucoid_sputum is highly correlated with family_historyHigh correlation
rusty_sputum is highly correlated with phlegm and 1 other fieldsHigh correlation
lack_of_concentration is highly correlated with dizziness and 1 other fieldsHigh correlation
visual_disturbances is highly correlated with acidity and 4 other fieldsHigh correlation
receiving_blood_transfusion is highly correlated with yellow_urine and 1 other fieldsHigh correlation
receiving_unsterile_injections is highly correlated with yellow_urine and 1 other fieldsHigh correlation
coma is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
stomach_bleeding is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
distention_of_abdomen is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
history_of_alcohol_consumption is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
fluid_overload.1 is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
blood_in_sputum is highly correlated with mild_fever and 2 other fieldsHigh correlation
prominent_veins_on_calf is highly correlated with cramps and 4 other fieldsHigh correlation
palpitations is highly correlated with anxiety and 3 other fieldsHigh correlation
painful_walking is highly correlated with knee_pain and 3 other fieldsHigh correlation
pus_filled_pimples is highly correlated with blackheads and 1 other fieldsHigh correlation
blackheads is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
scurring is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
skin_peeling is highly correlated with silver_like_dusting and 2 other fieldsHigh correlation
silver_like_dusting is highly correlated with skin_peeling and 2 other fieldsHigh correlation
small_dents_in_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
inflammatory_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
blister is highly correlated with red_sore_around_nose and 1 other fieldsHigh correlation
red_sore_around_nose is highly correlated with blister and 1 other fieldsHigh correlation
yellow_crust_ooze is highly correlated with blister and 1 other fieldsHigh correlation
dehydration is highly correlated with fluid_overload and 2 other fieldsHigh correlation
anxiety is highly correlated with blurred_and_distorted_vision and 5 other fieldsHigh correlation
rusty_sputum is highly correlated with fast_heart_rate and 3 other fieldsHigh correlation
yellowing_of_eyes is highly correlated with fluid_overload and 5 other fieldsHigh correlation
bruising is highly correlated with prominent_veins_on_calf and 6 other fieldsHigh correlation
high_fever is highly correlated with chills and 2 other fieldsHigh correlation
blurred_and_distorted_vision is highly correlated with anxiety and 11 other fieldsHigh correlation
movement_stiffness is highly correlated with painful_walking and 5 other fieldsHigh correlation
enlarged_thyroid is highly correlated with brittle_nails and 10 other fieldsHigh correlation
irritation_in_anus is highly correlated with pain_in_anal_region and 5 other fieldsHigh correlation
muscle_pain is highly correlated with fluid_overload and 1 other fieldsHigh correlation
swelling_of_stomach is highly correlated with fluid_overload.1 and 4 other fieldsHigh correlation
painful_walking is highly correlated with movement_stiffness and 5 other fieldsHigh correlation
sweating is highly correlated with fast_heart_rate and 3 other fieldsHigh correlation
spinning_movements is highly correlated with loss_of_balance and 3 other fieldsHigh correlation
brittle_nails is highly correlated with enlarged_thyroid and 10 other fieldsHigh correlation
fluid_overload.1 is highly correlated with swelling_of_stomach and 4 other fieldsHigh correlation
red_spots_over_body is highly correlated with malaise and 3 other fieldsHigh correlation
family_history is highly correlated with mucoid_sputum and 2 other fieldsHigh correlation
prominent_veins_on_calf is highly correlated with bruising and 6 other fieldsHigh correlation
spotting_ urination is highly correlated with stomach_pain and 3 other fieldsHigh correlation
polyuria is highly correlated with blurred_and_distorted_vision and 6 other fieldsHigh correlation
fast_heart_rate is highly correlated with rusty_sputum and 3 other fieldsHigh correlation
chest_pain is highly correlated with phlegm and 4 other fieldsHigh correlation
itching is highly correlated with fluid_overload and 1 other fieldsHigh correlation
belly_pain is highly correlated with fluid_overload and 3 other fieldsHigh correlation
malaise is highly correlated with red_spots_over_body and 5 other fieldsHigh correlation
stomach_pain is highly correlated with spotting_ urination and 3 other fieldsHigh correlation
weakness_of_one_body_side is highly correlated with altered_sensorium and 2 other fieldsHigh correlation
congestion is highly correlated with runny_nose and 9 other fieldsHigh correlation
altered_sensorium is highly correlated with weakness_of_one_body_side and 2 other fieldsHigh correlation
blister is highly correlated with red_sore_around_nose and 3 other fieldsHigh correlation
runny_nose is highly correlated with congestion and 9 other fieldsHigh correlation
weakness_in_limbs is highly correlated with loss_of_balance and 5 other fieldsHigh correlation
pain_in_anal_region is highly correlated with irritation_in_anus and 5 other fieldsHigh correlation
acidity is highly correlated with ulcers_on_tongue and 3 other fieldsHigh correlation
extra_marital_contacts is highly correlated with patches_in_throat and 3 other fieldsHigh correlation
joint_pain is highly correlated with fluid_overload and 1 other fieldsHigh correlation
depression is highly correlated with enlarged_thyroid and 9 other fieldsHigh correlation
chills is highly correlated with high_fever and 4 other fieldsHigh correlation
drying_and_tingling_lips is highly correlated with anxiety and 5 other fieldsHigh correlation
irregular_sugar_level is highly correlated with blurred_and_distorted_vision and 6 other fieldsHigh correlation
continuous_sneezing is highly correlated with congestion and 9 other fieldsHigh correlation
stiff_neck is highly correlated with movement_stiffness and 3 other fieldsHigh correlation
phlegm is highly correlated with rusty_sputum and 15 other fieldsHigh correlation
hip_joint_pain is highly correlated with painful_walking and 5 other fieldsHigh correlation
weight_gain is highly correlated with enlarged_thyroid and 10 other fieldsHigh correlation
bloody_stool is highly correlated with irritation_in_anus and 5 other fieldsHigh correlation
increased_appetite is highly correlated with blurred_and_distorted_vision and 6 other fieldsHigh correlation
shivering is highly correlated with continuous_sneezing and 3 other fieldsHigh correlation
pain_behind_the_eyes is highly correlated with red_spots_over_body and 3 other fieldsHigh correlation
receiving_blood_transfusion is highly correlated with yellow_urine and 3 other fieldsHigh correlation
muscle_weakness is highly correlated with movement_stiffness and 2 other fieldsHigh correlation
swollen_legs is highly correlated with bruising and 6 other fieldsHigh correlation
indigestion is highly correlated with internal_itching and 4 other fieldsHigh correlation
abnormal_menstruation is highly correlated with enlarged_thyroid and 9 other fieldsHigh correlation
blackheads is highly correlated with fluid_overload and 3 other fieldsHigh correlation
nodal_skin_eruptions is highly correlated with dischromic _patches and 2 other fieldsHigh correlation
ulcers_on_tongue is highly correlated with stomach_pain and 3 other fieldsHigh correlation
blood_in_sputum is highly correlated with phlegm and 4 other fieldsHigh correlation
mild_fever is highly correlated with blood_in_sputum and 3 other fieldsHigh correlation
irritability is highly correlated with blurred_and_distorted_vision and 6 other fieldsHigh correlation
loss_of_balance is highly correlated with spinning_movements and 6 other fieldsHigh correlation
restlessness is highly correlated with polyuria and 6 other fieldsHigh correlation
continuous_feel_of_urine is highly correlated with burning_micturition and 4 other fieldsHigh correlation
watering_from_eyes is highly correlated with continuous_sneezing and 3 other fieldsHigh correlation
cough is highly correlated with chest_pain and 4 other fieldsHigh correlation
distention_of_abdomen is highly correlated with swelling_of_stomach and 4 other fieldsHigh correlation
pain_during_bowel_movements is highly correlated with irritation_in_anus and 5 other fieldsHigh correlation
unsteadiness is highly correlated with spinning_movements and 3 other fieldsHigh correlation
yellow_urine is highly correlated with receiving_blood_transfusion and 3 other fieldsHigh correlation
mucoid_sputum is highly correlated with family_history and 2 other fieldsHigh correlation
coma is highly correlated with fluid_overload and 3 other fieldsHigh correlation
inflammatory_nails is highly correlated with fluid_overload and 4 other fieldsHigh correlation
loss_of_smell is highly correlated with congestion and 9 other fieldsHigh correlation
obesity is highly correlated with bruising and 9 other fieldsHigh correlation
internal_itching is highly correlated with indigestion and 3 other fieldsHigh correlation
fatigue is highly correlated with fluid_overload and 1 other fieldsHigh correlation
visual_disturbances is highly correlated with blurred_and_distorted_vision and 6 other fieldsHigh correlation
red_sore_around_nose is highly correlated with blister and 3 other fieldsHigh correlation
dischromic _patches is highly correlated with nodal_skin_eruptions and 2 other fieldsHigh correlation
patches_in_throat is highly correlated with extra_marital_contacts and 3 other fieldsHigh correlation
burning_micturition is highly correlated with spotting_ urination and 5 other fieldsHigh correlation
cramps is highly correlated with bruising and 6 other fieldsHigh correlation
breathlessness is highly correlated with sweating and 5 other fieldsHigh correlation
fluid_overload is highly correlated with dehydration and 131 other fieldsHigh correlation
knee_pain is highly correlated with painful_walking and 5 other fieldsHigh correlation
silver_like_dusting is highly correlated with inflammatory_nails and 4 other fieldsHigh correlation
constipation is highly correlated with irritation_in_anus and 7 other fieldsHigh correlation
receiving_unsterile_injections is highly correlated with receiving_blood_transfusion and 3 other fieldsHigh correlation
pus_filled_pimples is highly correlated with blackheads and 3 other fieldsHigh correlation
scurring is highly correlated with blackheads and 3 other fieldsHigh correlation
diarrhoea is highly correlated with fluid_overload and 1 other fieldsHigh correlation
swollen_blood_vessels is highly correlated with bruising and 6 other fieldsHigh correlation
slurred_speech is highly correlated with anxiety and 5 other fieldsHigh correlation
toxic_look_(typhos) is highly correlated with belly_pain and 3 other fieldsHigh correlation
abdominal_pain is highly correlated with yellowing_of_eyes and 4 other fieldsHigh correlation
mood_swings is highly correlated with enlarged_thyroid and 9 other fieldsHigh correlation
skin_peeling is highly correlated with inflammatory_nails and 4 other fieldsHigh correlation
weight_loss is highly correlated with restlessness and 2 other fieldsHigh correlation
muscle_wasting is highly correlated with extra_marital_contacts and 3 other fieldsHigh correlation
nausea is highly correlated with fluid_overload and 2 other fieldsHigh correlation
headache is highly correlated with fluid_overload and 1 other fieldsHigh correlation
passage_of_gases is highly correlated with indigestion and 3 other fieldsHigh correlation
throat_irritation is highly correlated with congestion and 9 other fieldsHigh correlation
redness_of_eyes is highly correlated with congestion and 9 other fieldsHigh correlation
small_dents_in_nails is highly correlated with inflammatory_nails and 4 other fieldsHigh correlation
dizziness is highly correlated with enlarged_thyroid and 10 other fieldsHigh correlation
prognosis is highly correlated with dehydration and 131 other fieldsHigh correlation
lethargy is highly correlated with fluid_overload and 1 other fieldsHigh correlation
swollen_extremeties is highly correlated with enlarged_thyroid and 10 other fieldsHigh correlation
palpitations is highly correlated with anxiety and 5 other fieldsHigh correlation
foul_smell_of urine is highly correlated with continuous_feel_of_urine and 4 other fieldsHigh correlation
lack_of_concentration is highly correlated with loss_of_balance and 3 other fieldsHigh correlation
cold_hands_and_feets is highly correlated with enlarged_thyroid and 10 other fieldsHigh correlation
bladder_discomfort is highly correlated with continuous_feel_of_urine and 4 other fieldsHigh correlation
sunken_eyes is highly correlated with dehydration and 2 other fieldsHigh correlation
acute_liver_failure is highly correlated with coma and 3 other fieldsHigh correlation
history_of_alcohol_consumption is highly correlated with swelling_of_stomach and 4 other fieldsHigh correlation
neck_pain is highly correlated with weakness_in_limbs and 4 other fieldsHigh correlation
loss_of_appetite is highly correlated with yellowing_of_eyes and 3 other fieldsHigh correlation
stomach_bleeding is highly correlated with coma and 3 other fieldsHigh correlation
vomiting is highly correlated with fluid_overload and 2 other fieldsHigh correlation
dark_urine is highly correlated with yellowing_of_eyes and 4 other fieldsHigh correlation
swelled_lymph_nodes is highly correlated with malaise and 11 other fieldsHigh correlation
puffy_face_and_eyes is highly correlated with enlarged_thyroid and 10 other fieldsHigh correlation
sinus_pressure is highly correlated with congestion and 9 other fieldsHigh correlation
skin_rash is highly correlated with fluid_overload and 1 other fieldsHigh correlation
swelling_joints is highly correlated with movement_stiffness and 5 other fieldsHigh correlation
back_pain is highly correlated with weakness_in_limbs and 3 other fieldsHigh correlation
yellowish_skin is highly correlated with yellowing_of_eyes and 5 other fieldsHigh correlation
yellow_crust_ooze is highly correlated with blister and 3 other fieldsHigh correlation
excessive_hunger is highly correlated with blurred_and_distorted_vision and 4 other fieldsHigh correlation
itching is highly correlated with spotting_ urination and 4 other fieldsHigh correlation
skin_rash is highly correlated with pain_behind_the_eyes and 2 other fieldsHigh correlation
nodal_skin_eruptions is highly correlated with dischromic _patches and 1 other fieldsHigh correlation
continuous_sneezing is highly correlated with shivering and 11 other fieldsHigh correlation
shivering is highly correlated with continuous_sneezing and 2 other fieldsHigh correlation
chills is highly correlated with continuous_sneezing and 21 other fieldsHigh correlation
joint_pain is highly correlated with dark_urine and 14 other fieldsHigh correlation
stomach_pain is highly correlated with acidity and 4 other fieldsHigh correlation
acidity is highly correlated with stomach_pain and 7 other fieldsHigh correlation
ulcers_on_tongue is highly correlated with stomach_pain and 4 other fieldsHigh correlation
muscle_wasting is highly correlated with patches_in_throat and 2 other fieldsHigh correlation
vomiting is highly correlated with nausea and 2 other fieldsHigh correlation
burning_micturition is highly correlated with stomach_pain and 5 other fieldsHigh correlation
spotting_ urination is highly correlated with itching and 3 other fieldsHigh correlation
fatigue is highly correlated with weight_loss and 4 other fieldsHigh correlation
weight_gain is highly correlated with cold_hands_and_feets and 11 other fieldsHigh correlation
anxiety is highly correlated with sweating and 7 other fieldsHigh correlation
cold_hands_and_feets is highly correlated with weight_gain and 11 other fieldsHigh correlation
mood_swings is highly correlated with weight_gain and 13 other fieldsHigh correlation
weight_loss is highly correlated with fatigue and 7 other fieldsHigh correlation
restlessness is highly correlated with mood_swings and 11 other fieldsHigh correlation
lethargy is highly correlated with fatigue and 13 other fieldsHigh correlation
patches_in_throat is highly correlated with muscle_wasting and 2 other fieldsHigh correlation
irregular_sugar_level is highly correlated with weight_loss and 8 other fieldsHigh correlation
cough is highly correlated with chills and 17 other fieldsHigh correlation
high_fever is highly correlated with chills and 7 other fieldsHigh correlation
sunken_eyes is highly correlated with dehydration and 2 other fieldsHigh correlation
breathlessness is highly correlated with cough and 7 other fieldsHigh correlation
sweating is highly correlated with chills and 11 other fieldsHigh correlation
dehydration is highly correlated with sunken_eyes and 2 other fieldsHigh correlation
indigestion is highly correlated with acidity and 7 other fieldsHigh correlation
headache is highly correlated with chills and 3 other fieldsHigh correlation
yellowish_skin is highly correlated with dark_urine and 5 other fieldsHigh correlation
dark_urine is highly correlated with joint_pain and 11 other fieldsHigh correlation
nausea is highly correlated with joint_pain and 7 other fieldsHigh correlation
loss_of_appetite is highly correlated with joint_pain and 9 other fieldsHigh correlation
pain_behind_the_eyes is highly correlated with skin_rash and 7 other fieldsHigh correlation
back_pain is highly correlated with pain_behind_the_eyes and 4 other fieldsHigh correlation
constipation is highly correlated with pain_during_bowel_movements and 6 other fieldsHigh correlation
abdominal_pain is highly correlated with vomiting and 6 other fieldsHigh correlation
diarrhoea is highly correlated with sunken_eyes and 5 other fieldsHigh correlation
mild_fever is highly correlated with loss_of_appetite and 6 other fieldsHigh correlation
yellow_urine is highly correlated with itching and 7 other fieldsHigh correlation
yellowing_of_eyes is highly correlated with joint_pain and 14 other fieldsHigh correlation
acute_liver_failure is highly correlated with joint_pain and 5 other fieldsHigh correlation
swelling_of_stomach is highly correlated with distention_of_abdomen and 3 other fieldsHigh correlation
swelled_lymph_nodes is highly correlated with continuous_sneezing and 16 other fieldsHigh correlation
malaise is highly correlated with chills and 22 other fieldsHigh correlation
blurred_and_distorted_vision is highly correlated with acidity and 16 other fieldsHigh correlation
phlegm is highly correlated with continuous_sneezing and 18 other fieldsHigh correlation
throat_irritation is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
redness_of_eyes is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
sinus_pressure is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
runny_nose is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
congestion is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
chest_pain is highly correlated with chills and 16 other fieldsHigh correlation
weakness_in_limbs is highly correlated with back_pain and 4 other fieldsHigh correlation
fast_heart_rate is highly correlated with mood_swings and 7 other fieldsHigh correlation
pain_during_bowel_movements is highly correlated with constipation and 4 other fieldsHigh correlation
pain_in_anal_region is highly correlated with constipation and 4 other fieldsHigh correlation
bloody_stool is highly correlated with constipation and 4 other fieldsHigh correlation
irritation_in_anus is highly correlated with constipation and 4 other fieldsHigh correlation
neck_pain is highly correlated with back_pain and 8 other fieldsHigh correlation
dizziness is highly correlated with weight_gain and 13 other fieldsHigh correlation
cramps is highly correlated with bruising and 5 other fieldsHigh correlation
bruising is highly correlated with cramps and 5 other fieldsHigh correlation
obesity is highly correlated with restlessness and 10 other fieldsHigh correlation
swollen_legs is highly correlated with cramps and 5 other fieldsHigh correlation
swollen_blood_vessels is highly correlated with cramps and 5 other fieldsHigh correlation
puffy_face_and_eyes is highly correlated with weight_gain and 11 other fieldsHigh correlation
enlarged_thyroid is highly correlated with weight_gain and 11 other fieldsHigh correlation
brittle_nails is highly correlated with weight_gain and 11 other fieldsHigh correlation
swollen_extremeties is highly correlated with weight_gain and 11 other fieldsHigh correlation
excessive_hunger is highly correlated with anxiety and 12 other fieldsHigh correlation
extra_marital_contacts is highly correlated with muscle_wasting and 2 other fieldsHigh correlation
drying_and_tingling_lips is highly correlated with anxiety and 7 other fieldsHigh correlation
slurred_speech is highly correlated with anxiety and 7 other fieldsHigh correlation
knee_pain is highly correlated with joint_pain and 5 other fieldsHigh correlation
hip_joint_pain is highly correlated with joint_pain and 5 other fieldsHigh correlation
muscle_weakness is highly correlated with mood_swings and 8 other fieldsHigh correlation
stiff_neck is highly correlated with acidity and 9 other fieldsHigh correlation
swelling_joints is highly correlated with neck_pain and 7 other fieldsHigh correlation
movement_stiffness is highly correlated with muscle_weakness and 4 other fieldsHigh correlation
spinning_movements is highly correlated with loss_of_balance and 2 other fieldsHigh correlation
loss_of_balance is highly correlated with weakness_in_limbs and 6 other fieldsHigh correlation
unsteadiness is highly correlated with spinning_movements and 2 other fieldsHigh correlation
weakness_of_one_body_side is highly correlated with altered_sensorium and 1 other fieldsHigh correlation
loss_of_smell is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
bladder_discomfort is highly correlated with burning_micturition and 3 other fieldsHigh correlation
foul_smell_of urine is highly correlated with burning_micturition and 3 other fieldsHigh correlation
continuous_feel_of_urine is highly correlated with burning_micturition and 3 other fieldsHigh correlation
passage_of_gases is highly correlated with indigestion and 2 other fieldsHigh correlation
internal_itching is highly correlated with indigestion and 2 other fieldsHigh correlation
toxic_look_(typhos) is highly correlated with chills and 4 other fieldsHigh correlation
depression is highly correlated with acidity and 15 other fieldsHigh correlation
irritability is highly correlated with weight_gain and 16 other fieldsHigh correlation
muscle_pain is highly correlated with chills and 11 other fieldsHigh correlation
altered_sensorium is highly correlated with weakness_of_one_body_side and 1 other fieldsHigh correlation
red_spots_over_body is highly correlated with skin_rash and 9 other fieldsHigh correlation
belly_pain is highly correlated with chills and 4 other fieldsHigh correlation
abnormal_menstruation is highly correlated with weight_gain and 13 other fieldsHigh correlation
dischromic _patches is highly correlated with nodal_skin_eruptions and 1 other fieldsHigh correlation
watering_from_eyes is highly correlated with continuous_sneezing and 2 other fieldsHigh correlation
increased_appetite is highly correlated with weight_loss and 8 other fieldsHigh correlation
polyuria is highly correlated with weight_loss and 8 other fieldsHigh correlation
family_history is highly correlated with mucoid_sputum and 1 other fieldsHigh correlation
mucoid_sputum is highly correlated with cough and 3 other fieldsHigh correlation
rusty_sputum is highly correlated with chills and 8 other fieldsHigh correlation
lack_of_concentration is highly correlated with dizziness and 2 other fieldsHigh correlation
visual_disturbances is highly correlated with acidity and 7 other fieldsHigh correlation
receiving_blood_transfusion is highly correlated with itching and 7 other fieldsHigh correlation
receiving_unsterile_injections is highly correlated with itching and 7 other fieldsHigh correlation
coma is highly correlated with joint_pain and 5 other fieldsHigh correlation
stomach_bleeding is highly correlated with joint_pain and 5 other fieldsHigh correlation
distention_of_abdomen is highly correlated with swelling_of_stomach and 3 other fieldsHigh correlation
history_of_alcohol_consumption is highly correlated with swelling_of_stomach and 3 other fieldsHigh correlation
fluid_overload.1 is highly correlated with swelling_of_stomach and 3 other fieldsHigh correlation
blood_in_sputum is highly correlated with chills and 11 other fieldsHigh correlation
prominent_veins_on_calf is highly correlated with cramps and 5 other fieldsHigh correlation
palpitations is highly correlated with anxiety and 7 other fieldsHigh correlation
painful_walking is highly correlated with neck_pain and 7 other fieldsHigh correlation
pus_filled_pimples is highly correlated with blackheads and 2 other fieldsHigh correlation
blackheads is highly correlated with pus_filled_pimples and 2 other fieldsHigh correlation
scurring is highly correlated with pus_filled_pimples and 2 other fieldsHigh correlation
skin_peeling is highly correlated with joint_pain and 4 other fieldsHigh correlation
silver_like_dusting is highly correlated with joint_pain and 4 other fieldsHigh correlation
small_dents_in_nails is highly correlated with joint_pain and 4 other fieldsHigh correlation
inflammatory_nails is highly correlated with joint_pain and 4 other fieldsHigh correlation
blister is highly correlated with red_sore_around_nose and 2 other fieldsHigh correlation
red_sore_around_nose is highly correlated with blister and 2 other fieldsHigh correlation
yellow_crust_ooze is highly correlated with blister and 2 other fieldsHigh correlation
prognosis is highly correlated with itching and 130 other fieldsHigh correlation
prognosis is uniformly distributed Uniform

Reproduction

Analysis started2022-02-14 08:25:04.243985
Analysis finished2022-02-14 08:27:29.522536
Duration2 minutes and 25.28 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

itching
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4242 
1
678 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
04242
86.2%
1678
 
13.8%

Length

2022-02-14T13:57:29.801678image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:29.883478image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04242
86.2%
1678
 
13.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

skin_rash
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4134 
1
786 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
04134
84.0%
1786
 
16.0%

Length

2022-02-14T13:57:30.714043image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:30.788149image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04134
84.0%
1786
 
16.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

nodal_skin_eruptions
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:30.859011image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:31.067180image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

continuous_sneezing
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Length

2022-02-14T13:57:31.179299image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:31.260578image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

shivering
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:31.331871image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:31.402684image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

chills
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4122 
1
798 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04122
83.8%
1798
 
16.2%

Length

2022-02-14T13:57:31.475943image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:31.539299image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04122
83.8%
1798
 
16.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

joint_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4236 
1
684 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04236
86.1%
1684
 
13.9%

Length

2022-02-14T13:57:31.617449image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:31.683197image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04236
86.1%
1684
 
13.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

stomach_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Length

2022-02-14T13:57:31.762839image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:31.872166image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

acidity
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Length

2022-02-14T13:57:31.940993image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:32.017233image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

ulcers_on_tongue
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:32.113982image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:32.225031image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

muscle_wasting
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:32.343396image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:32.416863image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vomiting
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3006 
1
1914 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03006
61.1%
11914
38.9%

Length

2022-02-14T13:57:32.489815image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:32.561685image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
03006
61.1%
11914
38.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

burning_micturition
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4704 
1
 
216

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04704
95.6%
1216
 
4.4%

Length

2022-02-14T13:57:32.639986image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:32.721693image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04704
95.6%
1216
 
4.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

spotting_ urination
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:32.802939image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:32.867878image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

fatigue
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
2988 
1
1932 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02988
60.7%
11932
39.3%

Length

2022-02-14T13:57:32.950786image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:33.014725image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
02988
60.7%
11932
39.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

weight_gain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:33.089843image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:33.157061image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

anxiety
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:33.247267image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:33.312419image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

cold_hands_and_feets
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:33.541085image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:33.610808image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

mood_swings
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-02-14T13:57:33.691579image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:33.759375image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

weight_loss
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4464 
1
456 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04464
90.7%
1456
 
9.3%

Length

2022-02-14T13:57:33.837601image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:33.908104image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04464
90.7%
1456
 
9.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

restlessness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-02-14T13:57:33.978029image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:34.041754image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

lethargy
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4464 
1
456 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04464
90.7%
1456
 
9.3%

Length

2022-02-14T13:57:34.118307image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:34.194393image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04464
90.7%
1456
 
9.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

patches_in_throat
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:34.266428image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:34.342441image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

irregular_sugar_level
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:34.429313image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:34.497931image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

cough
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4356 
1
564 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04356
88.5%
1564
 
11.5%

Length

2022-02-14T13:57:34.575270image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:34.654075image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04356
88.5%
1564
 
11.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

high_fever
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3558 
1
1362 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03558
72.3%
11362
 
27.7%

Length

2022-02-14T13:57:34.733160image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:34.800693image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
03558
72.3%
11362
 
27.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

sunken_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:34.867595image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:34.955508image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

breathlessness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4470 
1
450 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04470
90.9%
1450
 
9.1%

Length

2022-02-14T13:57:35.033745image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:35.101501image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04470
90.9%
1450
 
9.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

sweating
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4242 
1
678 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04242
86.2%
1678
 
13.8%

Length

2022-02-14T13:57:35.180854image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:35.257527image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04242
86.2%
1678
 
13.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

dehydration
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:35.320422image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:35.388524image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

indigestion
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Length

2022-02-14T13:57:35.462801image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:35.536189image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

headache
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3786 
1
1134 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03786
77.0%
11134
 
23.0%

Length

2022-02-14T13:57:35.620881image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:35.836937image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
03786
77.0%
11134
 
23.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

yellowish_skin
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4008 
1
912 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04008
81.5%
1912
 
18.5%

Length

2022-02-14T13:57:35.905647image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:35.981123image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04008
81.5%
1912
 
18.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

dark_urine
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4350 
1
570 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04350
88.4%
1570
 
11.6%

Length

2022-02-14T13:57:36.052717image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:36.137812image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04350
88.4%
1570
 
11.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

nausea
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3774 
1
1146 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03774
76.7%
11146
 
23.3%

Length

2022-02-14T13:57:36.205811image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:36.269630image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
03774
76.7%
11146
 
23.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

loss_of_appetite
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3768 
1
1152 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03768
76.6%
11152
 
23.4%

Length

2022-02-14T13:57:36.354289image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:36.423388image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
03768
76.6%
11152
 
23.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pain_behind_the_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:36.498263image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:36.575522image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

back_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-02-14T13:57:36.665356image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:36.747533image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

constipation
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-02-14T13:57:36.838882image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:36.922163image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

abdominal_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3888 
1
1032 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03888
79.0%
11032
 
21.0%

Length

2022-02-14T13:57:37.018361image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:37.089659image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
03888
79.0%
11032
 
21.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

diarrhoea
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4356 
1
564 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04356
88.5%
1564
 
11.5%

Length

2022-02-14T13:57:37.162246image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:37.232532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04356
88.5%
1564
 
11.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

mild_fever
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4566 
1
 
354

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04566
92.8%
1354
 
7.2%

Length

2022-02-14T13:57:37.305557image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:37.369551image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04566
92.8%
1354
 
7.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

yellow_urine
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:37.449684image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:37.512685image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

yellowing_of_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4104 
1
816 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04104
83.4%
1816
 
16.6%

Length

2022-02-14T13:57:37.587628image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:37.664135image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04104
83.4%
1816
 
16.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

acute_liver_failure
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:37.733438image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:37.802019image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

fluid_overload
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4920 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04920
100.0%

Length

2022-02-14T13:57:37.862255image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:37.939257image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04920
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swelling_of_stomach
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:38.172860image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:38.239244image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swelled_lymph_nodes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4572 
1
 
348

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04572
92.9%
1348
 
7.1%

Length

2022-02-14T13:57:38.317127image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:38.397099image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04572
92.9%
1348
 
7.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

malaise
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4218 
1
702 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04218
85.7%
1702
 
14.3%

Length

2022-02-14T13:57:38.459717image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:38.538884image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04218
85.7%
1702
 
14.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

blurred_and_distorted_vision
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4578 
1
 
342

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04578
93.0%
1342
 
7.0%

Length

2022-02-14T13:57:38.605980image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:38.672101image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04578
93.0%
1342
 
7.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

phlegm
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4566 
1
 
354

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04566
92.8%
1354
 
7.2%

Length

2022-02-14T13:57:38.755726image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:38.814960image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04566
92.8%
1354
 
7.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

throat_irritation
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:38.896146image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:38.975621image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

redness_of_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:39.039336image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:39.130263image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

sinus_pressure
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:39.228129image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:39.296905image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

runny_nose
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:39.377934image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:39.447041image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

congestion
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:39.536150image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:39.594863image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

chest_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4224 
1
696 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04224
85.9%
1696
 
14.1%

Length

2022-02-14T13:57:39.678334image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:39.747168image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04224
85.9%
1696
 
14.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

weakness_in_limbs
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:39.828698image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:39.893306image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

fast_heart_rate
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Length

2022-02-14T13:57:39.966316image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:40.033027image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pain_during_bowel_movements
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:40.104163image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:40.161379image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pain_in_anal_region
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:40.246698image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:40.463673image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

bloody_stool
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:40.534494image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:40.603802image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

irritation_in_anus
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:40.666844image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:40.745044image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

neck_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-02-14T13:57:40.819896image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:40.886865image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

dizziness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4584 
1
 
336

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04584
93.2%
1336
 
6.8%

Length

2022-02-14T13:57:40.958745image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:41.025508image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04584
93.2%
1336
 
6.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

cramps
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:41.095991image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:41.171305image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

bruising
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:41.247033image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:41.317954image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

obesity
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-02-14T13:57:41.396692image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:41.469980image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swollen_legs
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:41.560644image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:41.636563image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swollen_blood_vessels
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:41.698869image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:41.780436image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

puffy_face_and_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:41.878473image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:41.953808image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

enlarged_thyroid
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:42.033235image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:42.097574image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

brittle_nails
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:42.167747image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:42.246535image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swollen_extremeties
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:42.316245image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:42.386676image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

excessive_hunger
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4458 
1
462 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04458
90.6%
1462
 
9.4%

Length

2022-02-14T13:57:42.448953image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:42.532722image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04458
90.6%
1462
 
9.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

extra_marital_contacts
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:42.782621image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:42.884422image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

drying_and_tingling_lips
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:42.954991image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:43.030084image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

slurred_speech
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:43.096652image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:43.170316image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

knee_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:43.248456image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:43.318259image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

hip_joint_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:43.380738image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:43.470487image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

muscle_weakness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Length

2022-02-14T13:57:43.540471image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:43.612162image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

stiff_neck
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-02-14T13:57:43.680947image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:43.768024image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swelling_joints
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-02-14T13:57:43.856748image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:43.925926image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

movement_stiffness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:44.010666image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:44.081064image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

spinning_movements
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:44.135544image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:44.219882image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

loss_of_balance
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4578 
1
 
342

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04578
93.0%
1342
 
7.0%

Length

2022-02-14T13:57:44.294892image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:44.361757image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04578
93.0%
1342
 
7.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

unsteadiness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:44.432925image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:44.508553image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

weakness_of_one_body_side
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:44.566018image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:44.641471image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

loss_of_smell
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:44.725116image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:44.798596image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

bladder_discomfort
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:44.875145image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:45.098731image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

foul_smell_of urine
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4818 
1
 
102

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04818
97.9%
1102
 
2.1%

Length

2022-02-14T13:57:45.182001image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:45.252733image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04818
97.9%
1102
 
2.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

continuous_feel_of_urine
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:45.315620image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:45.382486image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

passage_of_gases
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:45.465080image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:45.529478image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

internal_itching
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:45.598648image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:45.672265image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

toxic_look_(typhos)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:45.760010image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:45.815166image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

depression
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Length

2022-02-14T13:57:45.897740image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:45.960532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

irritability
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4446 
1
474 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04446
90.4%
1474
 
9.6%

Length

2022-02-14T13:57:46.043743image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:46.118940image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04446
90.4%
1474
 
9.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

muscle_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4446 
1
474 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04446
90.4%
1474
 
9.6%

Length

2022-02-14T13:57:46.196258image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:46.283413image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04446
90.4%
1474
 
9.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

altered_sensorium
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:46.361246image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:46.429336image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

red_spots_over_body
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Length

2022-02-14T13:57:46.499317image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:46.575340image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

belly_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:46.667466image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:46.751204image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

abnormal_menstruation
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4680 
1
 
240

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04680
95.1%
1240
 
4.9%

Length

2022-02-14T13:57:46.822339image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:46.884277image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04680
95.1%
1240
 
4.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

dischromic _patches
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:46.969537image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:47.036608image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

watering_from_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:47.118815image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:47.185803image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

increased_appetite
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:47.264454image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:47.471076image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

polyuria
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:47.538930image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:47.615899image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

family_history
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-02-14T13:57:47.692452image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:47.824159image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

mucoid_sputum
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:47.899753image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:47.965401image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

rusty_sputum
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:48.059321image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:48.145241image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

lack_of_concentration
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:48.212481image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:48.276034image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

visual_disturbances
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:48.356631image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:48.425501image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

receiving_blood_transfusion
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:48.523556image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:48.592517image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

receiving_unsterile_injections
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:48.667073image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:48.742132image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

coma
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:48.815536image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:48.878752image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

stomach_bleeding
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:48.953338image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:49.008748image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

distention_of_abdomen
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:49.091397image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:49.158955image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

history_of_alcohol_consumption
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:49.236174image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:49.310275image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

fluid_overload.1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:49.375749image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:49.445959image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

blood_in_sputum
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:49.527638image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:49.611836image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

prominent_veins_on_calf
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:49.686695image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:49.909824image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

palpitations
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-02-14T13:57:49.970729image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:50.046439image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

painful_walking
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-02-14T13:57:50.121935image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:50.186439image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pus_filled_pimples
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:50.259043image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:50.341141image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

blackheads
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:50.412304image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:50.476717image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

scurring
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-02-14T13:57:50.547246image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:50.611642image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

skin_peeling
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:50.688195image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:50.768407image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

silver_like_dusting
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:50.852757image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:50.965953image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

small_dents_in_nails
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:51.046501image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:51.117522image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

inflammatory_nails
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:51.228271image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:51.296238image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

blister
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:51.407701image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:51.480354image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

red_sore_around_nose
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:51.569029image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:51.658911image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

yellow_crust_ooze
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-02-14T13:57:51.749900image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-02-14T13:57:51.848924image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

prognosis
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct41
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
Fungal infection
 
120
Hepatitis C
 
120
Hepatitis E
 
120
Alcoholic hepatitis
 
120
Tuberculosis
 
120
Other values (36)
4320 

Length

Max length39
Median length11
Mean length13.12195122
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFungal infection
2nd rowFungal infection
3rd rowFungal infection
4th rowFungal infection
5th rowFungal infection

Common Values

ValueCountFrequency (%)
Fungal infection120
 
2.4%
Hepatitis C120
 
2.4%
Hepatitis E120
 
2.4%
Alcoholic hepatitis120
 
2.4%
Tuberculosis120
 
2.4%
Common Cold120
 
2.4%
Pneumonia120
 
2.4%
Dimorphic hemmorhoids(piles)120
 
2.4%
Heart attack120
 
2.4%
Varicose veins120
 
2.4%
Other values (31)3720
75.6%

Length

2022-02-14T13:57:51.980271image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
hepatitis720
 
9.1%
infection240
 
3.0%
vertigo240
 
3.0%
fungal120
 
1.5%
asthma120
 
1.5%
chronic120
 
1.5%
cholestasis120
 
1.5%
drug120
 
1.5%
reaction120
 
1.5%
peptic120
 
1.5%
Other values (49)5880
74.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Correlations

2022-02-14T13:57:52.529644image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-02-14T13:57:57.170607image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-02-14T13:58:02.723524image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-02-14T13:58:09.253002image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-02-14T13:58:16.216067image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-02-14T13:57:24.045186image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

itchingskin_rashnodal_skin_eruptionscontinuous_sneezingshiveringchillsjoint_painstomach_painacidityulcers_on_tonguemuscle_wastingvomitingburning_micturitionspotting_ urinationfatigueweight_gainanxietycold_hands_and_feetsmood_swingsweight_lossrestlessnesslethargypatches_in_throatirregular_sugar_levelcoughhigh_feversunken_eyesbreathlessnesssweatingdehydrationindigestionheadacheyellowish_skindark_urinenausealoss_of_appetitepain_behind_the_eyesback_painconstipationabdominal_paindiarrhoeamild_feveryellow_urineyellowing_of_eyesacute_liver_failurefluid_overloadswelling_of_stomachswelled_lymph_nodesmalaiseblurred_and_distorted_visionphlegmthroat_irritationredness_of_eyessinus_pressurerunny_nosecongestionchest_painweakness_in_limbsfast_heart_ratepain_during_bowel_movementspain_in_anal_regionbloody_stoolirritation_in_anusneck_paindizzinesscrampsbruisingobesityswollen_legsswollen_blood_vesselspuffy_face_and_eyesenlarged_thyroidbrittle_nailsswollen_extremetiesexcessive_hungerextra_marital_contactsdrying_and_tingling_lipsslurred_speechknee_painhip_joint_painmuscle_weaknessstiff_neckswelling_jointsmovement_stiffnessspinning_movementsloss_of_balanceunsteadinessweakness_of_one_body_sideloss_of_smellbladder_discomfortfoul_smell_of urinecontinuous_feel_of_urinepassage_of_gasesinternal_itchingtoxic_look_(typhos)depressionirritabilitymuscle_painaltered_sensoriumred_spots_over_bodybelly_painabnormal_menstruationdischromic _patcheswatering_from_eyesincreased_appetitepolyuriafamily_historymucoid_sputumrusty_sputumlack_of_concentrationvisual_disturbancesreceiving_blood_transfusionreceiving_unsterile_injectionscomastomach_bleedingdistention_of_abdomenhistory_of_alcohol_consumptionfluid_overload.1blood_in_sputumprominent_veins_on_calfpalpitationspainful_walkingpus_filled_pimplesblackheadsscurringskin_peelingsilver_like_dustingsmall_dents_in_nailsinflammatory_nailsblisterred_sore_around_noseyellow_crust_oozeprognosis
0111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infection
1011000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infection
2101000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infection
3110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infection
4111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000Fungal infection
5011000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infection
6101000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infection
7110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infection
8111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000Fungal infection
9111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infection

Last rows

itchingskin_rashnodal_skin_eruptionscontinuous_sneezingshiveringchillsjoint_painstomach_painacidityulcers_on_tonguemuscle_wastingvomitingburning_micturitionspotting_ urinationfatigueweight_gainanxietycold_hands_and_feetsmood_swingsweight_lossrestlessnesslethargypatches_in_throatirregular_sugar_levelcoughhigh_feversunken_eyesbreathlessnesssweatingdehydrationindigestionheadacheyellowish_skindark_urinenausealoss_of_appetitepain_behind_the_eyesback_painconstipationabdominal_paindiarrhoeamild_feveryellow_urineyellowing_of_eyesacute_liver_failurefluid_overloadswelling_of_stomachswelled_lymph_nodesmalaiseblurred_and_distorted_visionphlegmthroat_irritationredness_of_eyessinus_pressurerunny_nosecongestionchest_painweakness_in_limbsfast_heart_ratepain_during_bowel_movementspain_in_anal_regionbloody_stoolirritation_in_anusneck_paindizzinesscrampsbruisingobesityswollen_legsswollen_blood_vesselspuffy_face_and_eyesenlarged_thyroidbrittle_nailsswollen_extremetiesexcessive_hungerextra_marital_contactsdrying_and_tingling_lipsslurred_speechknee_painhip_joint_painmuscle_weaknessstiff_neckswelling_jointsmovement_stiffnessspinning_movementsloss_of_balanceunsteadinessweakness_of_one_body_sideloss_of_smellbladder_discomfortfoul_smell_of urinecontinuous_feel_of_urinepassage_of_gasesinternal_itchingtoxic_look_(typhos)depressionirritabilitymuscle_painaltered_sensoriumred_spots_over_bodybelly_painabnormal_menstruationdischromic _patcheswatering_from_eyesincreased_appetitepolyuriafamily_historymucoid_sputumrusty_sputumlack_of_concentrationvisual_disturbancesreceiving_blood_transfusionreceiving_unsterile_injectionscomastomach_bleedingdistention_of_abdomenhistory_of_alcohol_consumptionfluid_overload.1blood_in_sputumprominent_veins_on_calfpalpitationspainful_walkingpus_filled_pimplesblackheadsscurringskin_peelingsilver_like_dustingsmall_dents_in_nailsinflammatory_nailsblisterred_sore_around_noseyellow_crust_oozeprognosis
4910000000000000001101100100000000000000000000000000000000000000000010000011110000000000000000000001100001000000000000000000000000000000Hypothyroidism
4911000000000000001000111000000010000000000010000000000000000010000000000000001000001000000000000000100001000000000000000000000000000000Hyperthyroidism
4912000000000001001010000000000010010010000000000000010000000000000000000000001011000000000000000000100000000000000000000000100000000000Hypoglycemia
4913000000100000000000000000000000000000000000000000000000000000000100000000000000110010000000000000000000000000000000000000010000000000Osteoarthristis
4914000000000000000000000000000000000000000000000000000000000000000000000000000000001111000000000000000000000000000000000000010000000000Arthritis
4915000000000001000000000000000000010010000000000000000000000000000000000000000000000000111000000000000000000000000000000000000000000000(vertigo) Paroymsal Positional Vertigo
4916010000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001110000000Acne
4917000000000000100000000000000000000000000000000000000000000000000000000000000000000000000001110000000000000000000000000000000000000000Urinary tract infection
4918010000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001111000Psoriasis
4919010000000000000000000000010000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000111Impetigo

Duplicate rows

Most frequently occurring

itchingskin_rashnodal_skin_eruptionscontinuous_sneezingshiveringchillsjoint_painstomach_painacidityulcers_on_tonguemuscle_wastingvomitingburning_micturitionspotting_ urinationfatigueweight_gainanxietycold_hands_and_feetsmood_swingsweight_lossrestlessnesslethargypatches_in_throatirregular_sugar_levelcoughhigh_feversunken_eyesbreathlessnesssweatingdehydrationindigestionheadacheyellowish_skindark_urinenausealoss_of_appetitepain_behind_the_eyesback_painconstipationabdominal_paindiarrhoeamild_feveryellow_urineyellowing_of_eyesacute_liver_failurefluid_overloadswelling_of_stomachswelled_lymph_nodesmalaiseblurred_and_distorted_visionphlegmthroat_irritationredness_of_eyessinus_pressurerunny_nosecongestionchest_painweakness_in_limbsfast_heart_ratepain_during_bowel_movementspain_in_anal_regionbloody_stoolirritation_in_anusneck_paindizzinesscrampsbruisingobesityswollen_legsswollen_blood_vesselspuffy_face_and_eyesenlarged_thyroidbrittle_nailsswollen_extremetiesexcessive_hungerextra_marital_contactsdrying_and_tingling_lipsslurred_speechknee_painhip_joint_painmuscle_weaknessstiff_neckswelling_jointsmovement_stiffnessspinning_movementsloss_of_balanceunsteadinessweakness_of_one_body_sideloss_of_smellbladder_discomfortfoul_smell_of urinecontinuous_feel_of_urinepassage_of_gasesinternal_itchingtoxic_look_(typhos)depressionirritabilitymuscle_painaltered_sensoriumred_spots_over_bodybelly_painabnormal_menstruationdischromic _patcheswatering_from_eyesincreased_appetitepolyuriafamily_historymucoid_sputumrusty_sputumlack_of_concentrationvisual_disturbancesreceiving_blood_transfusionreceiving_unsterile_injectionscomastomach_bleedingdistention_of_abdomenhistory_of_alcohol_consumptionfluid_overload.1blood_in_sputumprominent_veins_on_calfpalpitationspainful_walkingpus_filled_pimplesblackheadsscurringskin_peelingsilver_like_dustingsmall_dents_in_nailsinflammatory_nailsblisterred_sore_around_noseyellow_crust_oozeprognosis# duplicates
7000000000000000000000000000000000000000000000000000000000000000000000000000000001111000000000000000000000000000000000000010000000000Arthritis90
17000000000000000000000000000000000000001000000000000000000001111000000000000000000000000000000000000000000000000000000000000000000000Dimorphic hemmorhoids(piles)90
163000000100000000000000000000000000000000000000000000000000000000100000000000000110010000000000000000000000000000000000000010000000000Osteoarthristis84
252010000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001111000Psoriasis84
22000000000000000000000000000000000000010000000000000000000100000110000000000000000000010000000000000000000000000000000000000000000000Cervical spondylosis78
54000000000000001000000000000000001011000000010000000000000000000000000000000000000000000000000000000000000010000000000000000000000000Hepatitis C78
90000000000000100000000000000000000000000000000000000000000000000000000000000000000000000001110000000000000000000000000000000000000000Urinary tract infection78
100000000000001000000000000000000001000000100000010000000000000000000000000000000000000000000000000000000000000000000011100000000000000Alcoholic hepatitis78
105000000000001000000000000000000010000000000000000000000000000000000000000000000000000000100000000001000000000000000000000000000000000Paralysis (brain hemorrhage)78
110000000000001000000000000000000010010000000000000000000000000000000000000000000000000111000000000000000000000000000000000000000000000(vertigo) Paroymsal Positional Vertigo78